James: Unread How Research Uses Hypothesis, Criteria for Rejection of Null Hypothesis and Clinical Significance A hypothesis is a testable or calculable prediction or assumption about a population parameter based on insubstantial evidence. The population parameters include variance, standard deviation, and median. Hypothesis formulation requires testing, and this involves evaluations to determine the plausibility. A null hypothesis is formulated when a researcher suspects that there is no relationship between the variables in an observation and the purpose of the research would be to approve or refute such assumptions (Shreffler & Huecker, 2022). The researcher utilizes test statistics to compare the association or relationship between two or more variables by using hypothesis testing to calculate the coefficient of variation and determine if the regression relationship and the correlation coefficient are statistically significant. There are five stages of hypothesis testing which include determination of the null hypothesis, specifying the alternative hypothesis, setting the significance level, Calculating the test statistics and corresponding P-value, and drawing conclusion (Mishra & Alok, 2017). Research uses hypothesis testing in many ways which include measuring of the validity and reliability of outcomes in systematic investigation and to determine whether the data from the sample is statistically significant. It also provides a reliable framework for making any data decisions for population of interest by helping the researcher to successfully extrapolate data from the sample to the larger population. More importantly, hypothesis provides linkage to the underlying theory and specific research questions (Sancha & Panagiotakos, 2016). Meanwhile, the null hypothesis is rejected when the p-value is less than or equal to the significance level which refers to a criterion of judgment upon which a decision is made regarding the value stated in a null hypothesis (Paniagua, 2019). In relation to clinical practice, hypothesis testing validates the quality of research studies and increases the generality of findings thereby providing dependable knowledge for evidence-based practice and remains a valid prove concerning clinical issues, and patient education. REFERENCES Mishra, S. B. & Alok, S. (2017). Handbook of Research Methodology. Educreation Paniagua, F.A. (2019). The Null Hypothesis is Always Rejected with Statistical Tricks: Why a Do You Need it? Interamerican Journal of Psychology 6 (53), 17-27. DOI: 10.30849/rip/ijp.v53i1.1166 Sacha, V, & Panagiotakos, D. B. (2016). Insights in Hypothesis Testing and Making Decisions in Biomedical Research. Open Cardiovascular Medical Journal 10 (196), 200 DOI: 10.2174/1874192401610010196. PMID: 27733868 Shreffler, J. & Huecker, M.R. (2022). Hypothesis Testing, P Values, Confidence Intervals, and Significance. Retrieved From https://www.ncbi.nlm.nih.gov/books/NBK557421/
